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Detection of apple bruises caused by picking with the manipulator based on hyperspectral images

机译:通过基于高光谱图像拾取机械手引起的苹果瘀伤的检测

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The objective of this research was to investigate the potential of using hyperspectral images to detect Red Fuji apple bruises caused by picking with the manipulator. In the test, apples were hold by a manipulator and applied different forces. The contact areas of the apples to the manipulator were marked, and the hyperspectral images were taken, then the apples were stored in the refrigerator. The hyperspectral camera with the spectral region between 372 nm and 1007nm was used. A series of hyperspectral images were taken. Average gray values of pixels selected from the bruise region (contacted region) in the marked contact area and the normal region (non-contacted region) outside marked contact area were calculated and then calibrated to obtain thereflectance respectively. To find the relationship between bruises and the forces, the spectral characteristics from hyperspectral images of the apples applied different forces at the same time were compared. The spectral characteristics from the hyperspectral images of apples from different storing time were also compared to observe changes over time after the forces applied by the manipulator. In general, the reflectance data from bruise regions of the apple were generally lower than those from normal region on the same color side at the same storing time. The standard deviation of the mean gray value was calculated and then extracted the maximum and minimum value. The images at 420 nm, 588 nm, 674 nm, and 900nm were then combined to draw outline ofthe apple and find the bruise area.
机译:该研究的目的是研究使用高光谱图像检测通过与机械手拾取引起的红色富士苹果瘀伤的潜力。在测试中,苹果由机器人握住并施加不同的力量。标记苹果与操纵器的接触区域,并采取了高光谱图像,然后将苹果储存在冰箱中。使用具有372nm和1007m的光谱区域的高光谱相机。采取了一系列高光谱图像。计算从标记接触区域和正常区域(非接触区域)的褐色区域(接触区域)中选择的像素的平均灰度值,然后分别校准以获得其。为了找到瘀伤和力之间的关系,比较了苹果的高光谱图像的光谱特性,同时施加不同的力。还比较来自不同存储时间的苹果高光谱图像的光谱特性,以便在操纵器施加的力之后观察随时间的变化。通常,来自苹果的瘀伤区域的反射率数据通常低于来自相同存储时间的相同颜色侧的正常区域的数据。计算平均灰度值的标准偏差,然后提取最大值和最小值。然后将420nm,588nm,674nm和900nm的图像组合以绘制苹果的轮廓并找到瘀伤区域。

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